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Machine Learning Techniques For Multimedia: Case Studies On Organization And Retrieval
Libro 9 di 43: Cognitive TechnologiesDa: Basi6 International, Irving, TX, U.S.A.
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Machine Learning Techniques For Multimedia: Case Studies On Organization And Retrieval
Libro 9 di 43: Cognitive TechnologiesDa: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
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Machine Learning Techniques for Multimedia
Libro 9 di 43: Cognitive TechnologiesDa: Books Puddle, New York, NY, U.S.A.
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Machine Learning Techniques for Multimedia
Libro 9 di 43: Cognitive TechnologiesDa: Majestic Books, Hounslow, Regno Unito
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Aggiungi al carrelloCondizione: New. pp. xvi + 290 98 Illus.
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Machine Learning Techniques for Multimedia
Libro 9 di 43: Cognitive TechnologiesDa: Biblios, Frankfurt am main, HESSE, Germania
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Machine Learning Techniques For Adaptive Multimedia Retrieval: Technologies Applications And Perspectives (Premier Reference Source)
Lingua: Inglese
Editore: Information Science Reference, 2010
ISBN 10: 161692859X ISBN 13: 9781616928599
Da: Basi6 International, Irving, TX, U.S.A.
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Machine Learning Techniques For Multimedia
Libro 9 di 43: Cognitive TechnologiesDa: Basi6 International, Irving, TX, U.S.A.
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Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Machine Learning Techniques For Multimedia
Libro 9 di 43: Cognitive TechnologiesDa: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
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Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
Libro 9 di 43: Cognitive TechnologiesEUR 35,28
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Aggiungi al carrelloCondizione: Sehr gut. Zustand: Sehr gut | Seiten: 308 | Sprache: Englisch | Produktart: Bücher | Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations ¿ the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply. This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music.This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.
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Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval (Cognitive Technologies)
Libro 9 di 43: Cognitive TechnologiesDa: Ria Christie Collections, Uxbridge, Regno Unito
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Machine Learning Techniques for Adaptive Multimedia Retrieval: Technologies Applications and Perspectives
Lingua: Inglese
Editore: Information Science Reference, 2010
ISBN 10: 161692859X ISBN 13: 9781616928599
Da: Ria Christie Collections, Uxbridge, Regno Unito
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Machine Learning Techniques for Adaptive Multimedia Retrieval: Technologies Applications and Perspectives (Premier Reference Source)
Da: Mispah books, Redhill, SURRE, Regno Unito
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Machine Learning for Intelligent Multimedia Analytics: Techniques and Applications (Studies in Big Data)
Libro 82 di 95: Studies in Big DataDa: Ria Christie Collections, Uxbridge, Regno Unito
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Machine Learning for Intelligent Multimedia Analytics: Techniques and Applications (Studies in Big Data, 82)
Libro 82 di 95: Studies in Big DataDa: Ria Christie Collections, Uxbridge, Regno Unito
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Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval
Libro 9 di 43: Cognitive TechnologiesDa: LiLi - La Liberté des Livres, CANEJAN, Francia
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Aggiungi al carrelloCondizione: fine. l'article peut presenter de tres legers signes d'usure, petites rayures ou imperfections esthetiques. vendeur professionnel; envoi soigne en 24/48h.
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Machine Learning Techniques for Multimedia: Case Studies on.
Libro 9 di 43: Cognitive TechnologiesDa: Books Puddle, New York, NY, U.S.A.
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Machine Learning Techniques For Multimedia: Case Studies On Organization And Retrieval
Lingua: Inglese
Editore: Springer, 2008
Da: Books in my Basket, New Delhi, India
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Aggiungi al carrelloHardcover. Condizione: New. ISBN:9783540751700.
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Machine Learning Techniques for Multimedia | Case Studies on Organization and Retrieval
Libro 9 di 43: Cognitive TechnologiesEUR 140,00
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Machine Learning Techniques for Multimedia | Case Studies on Organization and Retrieval | Matthieu Cord (u. a.) | Taschenbuch | xvi | Englisch | 2014 | Springer | EAN 9783642443626 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Machine Learning for Intelligent Multimedia Analytics: Techniques and Applications (Studies in Big Data, 82)
Libro 82 di 95: Studies in Big DataDa: Books Puddle, New York, NY, U.S.A.
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Condizione: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
Libro 9 di 43: Cognitive TechnologiesLingua: Inglese
Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2008
ISBN 10: 354075170X ISBN 13: 9783540751700
EUR 160,49
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations - the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply. This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music.This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.
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Machine Learning for Intelligent Multimedia Analytics | Techniques and Applications
Libro 82 di 95: Studies in Big DataEUR 157,95
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Machine Learning for Intelligent Multimedia Analytics | Techniques and Applications | Pardeep Kumar (u. a.) | Taschenbuch | xiv | Englisch | 2022 | Springer | EAN 9789811594946 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
Libro 9 di 43: Cognitive TechnologiesLingua: Inglese
Editore: Springer, Berlin, Springer Berlin Heidelberg, Springer, 2014
ISBN 10: 3642443621 ISBN 13: 9783642443626
EUR 166,62
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations - the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply. This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music.This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.
-
Machine Learning for Intelligent Multimedia Analytics: Techniques and Applications (Studies in Big Data)
Libro 82 di 95: Studies in Big DataDa: Books Puddle, New York, NY, U.S.A.
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Condizione: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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Edizione InternazionaleMACHINE LEARNING TECHNIQUES FOR MULTIMEDIA: CASE STUDIES ON ORGANIZATION AND RETRIEVAL
Libro 9 di 43: Cognitive TechnologiesDa: UK BOOKS STORE, London, LONDO, Regno Unito
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EUR 234,95
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Aggiungi al carrelloHardcover. Condizione: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Edizione Internazionale
MACHINE LEARNING TECHNIQUES FOR ADAPTIVE MULTIMEDIA RETRIEVAL: TECHNOLOGIES APPLICATIONS AND PERSPECTIVESA
Da: UK BOOKS STORE, London, LONDO, Regno Unito
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Aggiungi al carrelloCondizione: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval (Cognitive Technologies)
Libro 9 di 43: Cognitive TechnologiesDa: Mispah books, Redhill, SURRE, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Machine Learning for Intelligent Multimedia Analytics : Techniques and Applications
Libro 82 di 95: Studies in Big DataLingua: Inglese
Editore: Springer Nature Singapore, Springer Nature Singapore, 2021
ISBN 10: 9811594910 ISBN 13: 9789811594915
EUR 188,08
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents applications of machine learning techniques in processing multimedia large-scale data. Multimedia such as text, image, audio, video, and graphics stands as one of the most demanding and exciting aspects of the information era. The book discusses new challenges faced by researchers in dealing with these large-scale data and also presents innovative solutions to address several potential research problems, e.g., enabling comprehensive visual classification to fill the semantic gap by exploring large-scale data, offering a promising frontier for detailed multimedia understanding, as well as extract patterns and making effective decisions by analyzing the large collection of data.
